Articles by Mauro Cesa
What quant finance can learn from a 240-year-old problem
Optimal transport theory offers a data-driven way to calibrate derivatives pricing models
Podcast: Matthew Dixon on decomposition of portfolio risk
New approach calculates contributions to value-at-risk for nonlinear portfolios
Podcast: Man Group’s Zohren on forecasting prices with DeepLOB
Deep learning model can project prices around 100 ticks into the future
Follow the moneyness
Barclays quants extend Bergomi’s skew stickiness ratio to all strikes
Estimating loan loss provisions may have just got easier
Commerzbank quant proposes shortcut to calculate lifetime loan loss reserves
Podcast: Antonov on pricing not-so-vanilla rates products
New model makes it easier to coherently price correlated derivatives
‘Signatures’ promise quants a tool for all jobs
Little-known mathematical technique could find applications from pricing options to sniffing out alpha signals
An ‘optimal’ way to calculate future P&L distributions?
Quants use neural networks to upgrade classic options pricing model
After Archegos, a bigger role for XVA desks?
Credit Suisse has stalled on call to expand XVA remit; others think it would have helped, but disagree on how
Podcast: turbo-charging derivatives pricing
Quants achieve more speed by reducing number of dimensions in price calculations
Machines can read, but do they understand?
A novel NLP application built on a Google transformer model can help predict ratings transitions
Podcast: NYU’s Kolm on transaction costs and machine learning
TCA methodologies that ignore partial fills “might be off by 20% to 30%”
Podcast: Colin Turfus on short-rate models and Libor’s end
Deutsche Bank quant proposes a lean model to quickly produce benchmark prices
Derivatives pricing starts feeling the heat of climate change
Quants find physical and transition risks can lead to significant rise in CVA
Podcast: Claudio Albanese on how bad models survive
Darwin’s theory of natural selection could help quants detect flawed models and strategies
The case for reinforcement learning in quant finance
The technology behind Google’s AlphaGo has been strangely overlooked by quants
Deep XVAs and the promise of super-fast pricing
Intelligent robots can value complex derivatives in minutes rather than hours
Synthetic data enters its Cubist phase
Quants are using the theory of rough paths to distil the essence of financial datasets
Podcast: Piterbarg on medians and machine learning
How the Libor transition inspired NatWest quant’s latest paper on exotic derivatives valuation
Podcast: Hagan on convexity, volatility and the London Whale
Ex-JP Morgan quant discusses his latest work and the risk failures that cost the bank $6bn in 2012
Podcast: Barclays’ Ben Burnett on how banks can implement HVA
New valuation adjustment may lead to more efficient management of derivatives books
A look at future exposures, through a 19th century lens
Can a centenarian maths idea speed up the calculation of forward sensitivities?
The volatility paradigm that’s stirring up options pricing
‘Rough volatility’ models promise better pricing and hedging of options. But will they catch on?
Deep hedging strays when volatility gets rough – study
In the most realistic simulations, data-driven approach fared 30% worse than conventional hedging